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2017 #SMSociety Theme: Social Media for Social Good or Evil

Our online behaviour is far from virtual–it extends our offline lives. Much social media research has identified the positive opportunities of using social media; for example, how people use social media to form support groups online, participate in political uprising, raise money for charities, extend teaching and learning outside the classroom, etc. However, mirroring offline experiences, we have also seen social media being used to spread propaganda and misinformation, recruit terrorists, live stream criminal activities, reinforce echo chambers by politicians, and perpetuate hate and oppression (such as racist, sexist, homophobic, and anti-Semitic behaviour).

Sunday, July 30 • 11:01 - 12:30
Stance Classification Of Twitter Debates: The Encryption Debate As A Use Case [FULL]

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Authors: Aseel Addawood, Jodi Schneider and Masooda Bashir

Abstract: Social media have enabled a revolution in user-generated content. They allow users to connect, build community, produce and share content, and publish opinions. To better understand online users’ attitudes and opinions, we use stance classification. Stance classification is a relatively new and challenging approach to deepen opinion mining by classifying a user's stance in a debate. Our stance classification use case is tweets that were related to the spring 2016 debate over the FBI’s request that Apple decrypt a user’s iPhone. In this “encryption debate,” public opinion was polarized between advocates for individual privacy and advocates for national security. We propose a machine learning approach to classify stance in the debate, and a topic classification that uses lexical, syntactic, Twitter-specific, and argumentative features as a predictor for classifications. Models trained on these feature sets showed significant increases in accuracy relative to the baseline.

Sunday July 30, 2017 11:01 - 12:30
TRS 1-073 - 7th Flr Ted Rogers School of Management, Ryerson University 55 Dundas Street West, Toronto, ON M5G 2C4

Attendees (6)